Career Guideline
Location
Hyderabad | India
Job description
Hiring for - Biostatistician DA TL & TM , SDM
Location - Pan India Hybrid Mode US Night shifts Data Analyst : 3+yrs of exp in Biostatistician , ctc upto 16lpa Team lead : Minimum 5+yrs of exp in Biostatistician , ctc upto 22lpa Team Manager : 6+yrs of exp in Biostatistician , ctc upto 30lpa SDM : 10yrs of exp in Biostatistician , ctc upto 40lpa Requires 5+ years of relevant research/clinical/healthcare experience (2 less years required with PhD) Masters degree in Statistics / Biostatistics or Applied Statistics Ph.D. preferred Skills : #Biostistician, #MockShell, #Statisticalanalysis, #Modellingtable, #Biostatistician,#Linearregression. #Logisticregression, #Ttest knowledge, #Anova knowledge, #Ancova knowledge Key Responsibilities Preparation & Review of Sap & Mock shell Evaluates research concepts to develop appropriate statistical methods of analysis Reviews protocols, writes statistical sections and Statistical Analysis Plans (SAPs) for assigned studies Determines methods of statistical analysis and applies statistical techniques to determine measures of central tendency, correlation, sample size, significance of difference, etc. Reviews CRFs and ensures complete data collection for analysis Runs randomization lists Prepares tables, charts, and graphs showing the results of statistical analysis Performs specialized statistical analysis involving correlation equations for multi-factorial variances and regression equations. Discusses study conduct and results with physicians and sponsors Detailed knowledge of SAS programming and procedures and other statistical software; writes edit checks in SAS; validates SAS programs Responsible for data transfer Ability to provide technical solutions to a wide range of difficult problems Works with research staff to resolve issues regarding data capture, accuracy, and completeness Assists in the development of new statistical tools and modeling protocols Documents methods, instructions and rules for implementing new techniques and research tools Develops standard data quality review checks and validation procedures Designs predictive modeling programming for evaluating health outcomes, utilization, and costs Produces standard error analysis routines and protocols (missing data & data errors checks) Diversifies research techniques, by producing mixed qualitative-quantitative approaches to evaluating EHRs. Advanced SAS programming skills for data manipulation (macros, proc SQL, data and proc steps, merging, use of first & last from proc sort, removal of duplicates, running totals, merging, use of arrays, proc template Interested candidates contact HR Umme @8655884775 / [email protected]Job tags
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